Phizenix4mo ago

Sr. Data Engineer, Data Analytics & Reporting

United States·San Franciscosenior

Data EngineeringData EngineerDataData & AI

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Quick Summary

Overview

We are seeking a Senior Data Engineer to support data analytics and platform initiatives. This role is ideal for a hands-on consultant who can build scalable data pipelines and enable analytics platforms across the organization.

Key Responsibilities

Build and maintain scalable data pipelines using modern data integration tools. Develop and optimize Snowflake-based data warehouses for performance and cost efficiency.

Requirements Summary

Strong hands-on experience with Snowflake & ETL Solid experience enabling analytics platforms such as Power BI. Strong communication skills and stakeholder-facing experience. Experience working across multiple data sources and enterprise systems.

Technical Tools

Data EngineeringData EngineerDataData & AI

Client is looking for a Sr. Data Engineer to lead the Data Analytics & Engineering function supporting our portfolio. You will define and execute the data and analytics strategy that enables trusted insights, build reporting & analytics that will supports decision-making across business functions across. This role blends strategic data leadership, data engineering and reporting experience, and strong business partnership, with accountability for delivering scalable, secure, and consumer.

Key Responsibilities

Architect, build, and optimize scalable enterprise data solutions on Snowflake, ensuring performance, reliability, and security across the data ecosystem.
Design and maintain modern data warehouse, data mart, and semantic layer architectures that support trusted, business-ready analytics.
Develop and manage robust ELT/ETL pipelines using FiveTran, dbt, Airflow, and related technologies to deliver high-quality, governed data.
Establish data quality, observability, lineage, monitoring, and governance frameworks that ensure accuracy and trust in enterprise data assets.
Create and manage semantic models that standardize business metrics, KPIs, and reporting definitions across the organization.
Partner with business, analytics, and technology stakeholders to translate complex requirements into scalable data products and self-service analytics solutions.
Design and deliver executive dashboards, reports, and visual analytics in Power BI that drive strategic and operational decision-making.
Collaborate with marketing, DTC, Digital Product, Commercial teams, and clean room partners to enable privacy-safe data sharing, audience insights, attribution, and customer analytics.
Lead data integration and modeling efforts across customer, digital, retail media, advertising, and enterprise platforms to create a unified view of business performance.
Champion engineering excellence through architecture leadership, best practices, mentoring, innovation, and continuous improvement of the modern data platform.
Establish and co-lead the Unilever Prestige Data Governance Council with brand technology leaders to establish data governance and quality frameworks.
Partner with Security, Privacy, and Legal teams to ensure compliance with data privacy, access controls, retention, and regulatory requirements.

Qualifications

8+ years of experience in Data Engineering, Analytics Engineering, Business Intelligence, or related fields.
Deep expertise with Snowflake architecture, performance optimization, security, and data modeling.
Proven experience building enterprise data warehouses and dimensional models.
Strong experience designing and implementing semantic models and business metric layers.
Hands-on expertise with Power BI, including data modeling, dashboard development, and enterprise reporting.
Experience building and maintaining ELT/ETL pipelines using FiveTran and similar data integration platforms.
Advanced SQL skills and strong understanding of data transformation frameworks.
Experience working with cloud-based data ecosystems.
Strong understanding of data governance, privacy, security, and compliance principles.
Experience partnering with business stakeholders and translating requirements into scalable data solutions.

What Success Looks Like - In your first year, you will:

Elevate Client's Snowflake environment into a trusted, scalable enterprise data platform.
Establish standardized semantic models and KPI definitions across the organization.
Deliver executive reporting experiences that drive strategic decisions.
Expand privacy-safe data collaboration capabilities through clean room integrations.
Improve data accessibility, quality, reliability, and self-service adoption.
Create a foundation for advanced analytics, AI, and future data product innovation.